Triple
T15598260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana de Velasco y Girón |
E374962
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Velasco |
E612422
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Velasco | Statement: [Ana de Velasco y Girón, familyName, Velasco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Velasco Context triple: [Ana de Velasco y Girón, familyName, Velasco]
-
A.
Velasco
chosen
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
-
B.
Vásquez
Vásquez is a Spanish-language surname common in Latin America and Spain, borne by numerous notable figures in sports, politics, and the arts.
-
C.
Carrillo
Carrillo is a Spanish-origin surname borne by numerous notable individuals across the Spanish-speaking world and beyond.
-
D.
Montúfar
Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
-
E.
Aparicio
Aparicio is a Spanish-language surname borne by various notable individuals across fields such as film, sports, and politics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e609ab081909feb486a57439960 |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ecba8d08190998fc0688663a328 |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 4:12 a.m.